Build and optimize low-level software for Cerebras’s AI-accelerated systems, working across hardware interfaces, networking, distributed infrastructure, and compilers. The role targets 2026 graduates with C/C++ proficiency and an interest in systems programming, performance, and hardware-software integration.
Salary not listed
HybridEntry levelEmbedded Engineering
About the role
Responsibilities
Collaborate with experienced engineers on systems and infrastructure challenges.
Design, implement, test, and debug software solutions affecting system performance and reliability.
Contribute to low-level software components interacting with hardware and networking infrastructure.
Work across layers of an AI-accelerated platform, including hardware interfaces, distributed systems, compilers, and ML frameworks.
Participate in debugging, performance optimization, and system bring-up activities.
Develop tools and infrastructure to improve observability, reliability, and scalability.
Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.
Requirements
Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, graduating in 2026.
Proficiency in C/C++ programming languages.
Interest or exposure to systems or socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.
Desire to work close to hardware and networks and learn low-level engineering concepts.
Detail-oriented, with willingness to learn broadly and step outside a comfort zone.
Excellent communication and collaboration skills.
Nice-to-haves
Experience with Linux systems programming or debugging tools.
Familiarity with TCP/RDMA protocols, RPCs, and packet-trace tools such as Wireshark.
Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.
Familiarity with performance optimization or concurrent programming concepts.
Interest in large-scale AI infrastructure and accelerated computing systems.
Compensation and Benefits
Hybrid role based in Toronto, ON, or Sunnyvale, CA.
Opportunity to work on an AI-accelerated platform, publish and open-source AI research, and contribute to high-performance computing infrastructure.
Startup vitality, job stability, and a non-corporate work culture emphasizing learning, growth, and support.
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